CN108624692B - Gene marker for screening benign and malignant pulmonary nodules and application thereof - Google Patents

Abstract

The invention discloses a group of genetic markers for screening benign and malignant pulmonary nodules, which comprise: the lung cancer characteristic genes shown in SEQ ID NO. 1-SEQ ID NO.12 are significantly and differentially expressed in peripheral blood of a patient with the micro-nodule lung cancer and a patient without the lung cancer. The invention also discloses application of the gene marker or any combination thereof in preparing a product for screening early lung cancer. The gene marker is used for early screening of high-risk lung cancer, has high sensitivity and strong specificity, takes peripheral blood which is most easily collected clinically as a detection sample, has a non-invasive and simple sampling mode and high detection compliance, is particularly suitable for matching with imaging detection modes such as CT and the like to be used for screening of super-early lung cancer of large-scale crowds, and has wide application prospect.

Description

Gene marker for screening benign and malignant pulmonary nodules and application thereof

Technical Field

The invention relates to the technical field of molecular biology, in particular to a gene marker for screening benign and malignant pulmonary nodules and application thereof.

Background

According to annual identification data counted by the ministry of health in 2011, the death rate of lung cancer in 2010 in China is 46.46 people/10 ten thousand people, and the death rate of the resident malignant tumor is the first number and is almost equal to the sum of the death rates of liver cancer, gastric cancer and large intestine cancer. The prognosis of lung cancer is closely related to clinical stages in definite diagnosis, wherein the treatment effect on the early-stage 0-stage peripheral in-situ lung cancer is the best, and the 5-year survival rate of a patient after operation is as high as 90%; the 5-year survival rate after surgery for stage Ia lung cancer is 61%, while the overall 5-year survival rate for stage II-IV patients decreases from 34% to less than 5%. Therefore, the key point for improving the cure rate of the lung cancer and reducing the mortality is early discovery, and especially the realization of the ultra-early discovery of the peripheral in-situ lung cancer at the 0 stage has important value for improving the cure rate of the lung cancer.

The current method of high resolution imaging examination such as low dose helical CT (LDCT) is a main means for early screening of lung cancer. In large-scale early lung cancer screening practice, a large number of patients with micro-nodules (the size of the nodules is less than 10mm) are found, the micro-nodules can be benign lesions of lung cancer such as inflammation and the like, and can also be micro-nodules lung cancer (about 30% -40%) containing malignant cancer cells, wherein most of the micro-nodules lung cancer belongs to ultra-early peripheral in situ lung cancer (the TNM stage of tumor is 0) and part of stage Ia lung cancer, and if early diagnosis can be carried out, a good treatment effect can be achieved. However, the clinical judgment of the benign and malignant properties of the pulmonary nodules is very difficult at present, mainly because the sizes of the pulmonary nodules are less than 10mm, biopsy sampling and pathological examination are difficult to perform through fine needle puncture and the like, and the diagnostic value of the obtained results is very limited even if PET-CT examination is performed. Other serum tumor markers related to lung cancer, such as carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), squamous cell carcinoma antigen (SCC-Ag), cytokeratin 19 fragment and the like, have a certain reference value for auxiliary diagnosis of middle and late stage lung cancer, but have little value for diagnosis of early stage lung cancer, particularly early stage peripheral in situ lung cancer (stage 0) and stage Ia lung cancer. In addition, the conventional tumor serum protein marker is usually low in detection sensitivity, for example, the detection sensitivity (positive detection rate) of CEA and NSE for middle and advanced lung cancer is generally only about 30%, the specificity of the serum protein marker for lung cancer detection is also poor, and other benign lesions such as pneumonia can cause abnormal concentration of the protein marker, resulting in false positive detection results. Therefore, in order to accurately identify the benign and malignant characteristics of the micro nodules detected by the CT imaging examination and to detect the early-stage micro-nodule lung cancer, a detection technology and a product capable of accurately identifying the benign and malignant characteristics of the micro nodules are required.

Blood is the largest tissue organ of the human body, and blood cells are few, and are cell types capable of exchanging information with almost all tissue cells. When malignant diseases such as injury, inflammation and tumor of tissues and organs in vivo occur, a series of specific changes of microenvironment around cells of diseased tissues occur. When blood flows through each tissue organ, the microenvironment of pathological tissue cells exchanges information with blood cells, and the blood cells directly or indirectly respond to the changes to generate corresponding gene expression changes to participate in information transmission and exchange of various systemic systems such as immune system. This change in gene expression in blood cells is far before the body produces a clear sign change and contains some gene expression changes characteristic of the disease. Therefore, by closely monitoring the expression profile of blood cell genes, molecular information of early malignant diseases such as in vivo tumors and the like can be sensitively captured, and gene expression signals (markers) characteristic to the diseases are screened out, so that reliable evidence is provided for early detection and monitoring of the diseases. And peripheral blood gene expression detection is used as a simple and noninvasive detection mode, so that the detection is easy to accept by a detected person, the detection compliance is high, and the method has great application value for early screening/diagnosis of malignant tumors.

Disclosure of Invention

The invention aims to solve the technical problem that a biomarker for accurately identifying benign and malignant pulmonary nodules is lacking clinically at present, and provides a peripheral blood gene marker for identifying benign and malignant pulmonary nodules, which can accurately identify malignant pulmonary nodules and discover ultra-early lung cancer, has high detection sensitivity and specificity, only needs to collect 2ml of peripheral venous blood for detection, is simple and convenient in detection process, and is particularly suitable for matching with imaging detection modes such as CT (computed tomography) and the like to be used for screening the ultra-early lung cancer of large-scale people.

In order to solve the technical problems, the invention is realized by the following technical scheme:

in one aspect of the invention, there is provided a product comprising one or more polynucleotides, or fragments thereof, which are differentially expressed in peripheral blood of a patient with minimal node lung cancer and a patient with non-lung cancer, the polynucleotides comprising at least one of the 12 lung cancer signature gene sequences HSP90AA1, UQCRQ, COX7a2, CAPZA2, CHMP5, NDUFB2, RPL24, CKLF, C14orf2, CD52, FGFBP2, GLRX as shown in SEQ ID No. 1-SEQ ID No. 12.

Preferably, the product comprises a plurality of polynucleotides or fragments thereof, and the polynucleotides comprise 6-12 lung cancer characteristic gene sequences in lung cancer characteristic gene sequences shown in SEQ ID NO. 1-SEQ ID NO. 12.

The micro-node non-lung cancer patients comprise benign lung lesion patients and healthy people.

In another aspect of the present invention, there is provided a composition comprising primers and/or probes for detecting differential expression of genes comprising at least one of the sequences of the characteristic genes of small nodule lung cancer as shown in SEQ ID No.1 to SEQ ID No.12 in peripheral blood of patients with small nodule lung cancer and non-lung cancer.

The probe comprises: (1) a polynucleotide, or fragment thereof, that specifically hybridizes to a transcript of gene expression; (2) a polypeptide binding agent such as an antibody, or fragment thereof, that specifically binds to a translation product of gene expression.

In another aspect of the invention, the use of the product comprising one or more polynucleotides or fragments thereof for preparing a product for the differential diagnosis or screening of very early lung cancer is also provided.

Preferably, the product for the differential diagnosis or screening of the ultra-early lung cancer comprises: and detecting the product of the micro-nodular lung cancer by using real-time quantitative PCR, RNA sequencing or gene chips.

The product for differential diagnosis or screening of the ultra-early lung cancer by using real-time quantitative PCR comprises a primer for specific amplification of at least one lung cancer characteristic gene sequence in the small-nodule lung cancer characteristic gene sequences shown in SEQ ID NO. 1-SEQ ID NO. 12.

The product for detecting, differentially diagnosing or screening the ultra-early lung cancer by using the gene chip comprises: and the probe is hybridized with at least one lung cancer characteristic gene sequence in the small-nodule lung cancer characteristic gene sequences shown in SEQ ID NO. 1-SEQ ID NO. 12.

In another aspect of the invention, the invention also provides a detection kit for the differential diagnosis or screening of the ultra-early lung cancer, and the kit comprises a primer and/or a probe specific to at least one lung cancer characteristic gene sequence in the minimal node lung cancer characteristic gene sequences shown in SEQ ID NO. 1-SEQ ID NO. 12. The kit also comprises primers and/or probes specific for the GAPDH reference gene sequence.

Preferably, the kit further comprises a fluorescent probe specifically bound to the PCR amplified fragment or a non-specifically bound SYBR Green dye.

Preferably, the primer comprises any one or more than two pairs of primer sequences shown in SEQ ID NO. 13-SEQ ID NO.36, and the probe comprises any one or more than two pairs of probe sequences shown in SEQ ID NO. 37-SEQ ID NO. 48; the primer and/or probe of the internal reference gene sequence is shown in SEQ ID NO. 48-SEQ ID NO. 51.

In another aspect of the present invention, a detection chip for the differential diagnosis or screening of the very early lung cancer is also provided, wherein the chip comprises a probe hybridized with at least one lung cancer characteristic gene sequence in the minimal node lung cancer characteristic gene sequences shown in SEQ ID No. 1-SEQ ID No. 12.

The kit or the detection chip can detect the expression condition of the characteristic gene sequences of the micro-nodule lung cancer shown by SEQ ID NO. 1-SEQ ID NO.12 in the peripheral blood of a detected person, and then input the micro-nodule lung cancer discrimination model according to the information of up-regulation or down-regulation of expression to obtain the risk value of the micro-nodule lung cancer of the detected person, thereby realizing early screening and diagnosis of the lung cancer.

The gene marker can be used for screening benign and malignant lung micro-nodules, has higher detection sensitivity and stronger specificity on the ultra-early micro-nodule lung cancer, is noninvasive in sampling mode and convenient to detect due to the fact that peripheral blood which is most easily collected clinically is used as a detection sample, is suitable for large-scale crowd screening and early diagnosis of the lung cancer, promotes early discovery of the lung cancer, improves the cure rate of the lung cancer, and has wide application prospect.

Drawings

The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.

FIG. 1 is a significant differential expression diagram of 12 selected genes for characterizing the micro-node lung cancer in example 1 of the present invention;

FIG. 2 is a Box Plot (Box-while Plot) of the screening of the small-node lung cancer (LungCa), Benign pulmonary node (Benign) and healthy Control (Control) samples by using 6 selected small-node lung cancer characteristic gene combinations (6-gene Panel) in example 2 of the present invention, and a prediction result list of the small-node lung cancer discriminant model for different grouped samples (Training Set and Test Set) and small-node lung cancers of different sizes, wherein the 6-gene Panel combination comprises: CKLF, GLRX, HSP90AA1, NDUFB2, RPL24, UQCRQ and other 6 lung cancer characteristic genes.

Detailed Description

Aiming at the technical blank that the good and malignant screening of pulmonary micro-nodules (the size of the nodules is less than 10mm) is difficult to realize clinically at present, the invention provides a gene marker combination for the good and malignant screening of the pulmonary micro-nodules. Based on quantitative detection of peripheral blood gene expression profiles, the invention screens 12 characteristic significant differential expression genes of lung cancer from peripheral blood gene expression profiles by quantitatively analyzing gene expression differences of peripheral blood total RNA of micro-nodule patients (including benign lung lesions and micro-nodule lung cancer patients, wherein the nodule sizes of all the patients are less than or equal to 10mm) and healthy people without lung lesions, and constructs corresponding micro-nodule lung cancer prediction models according to different gene combination products. Then, the relative expression quantity of the micro-nodule lung cancer gene marker in the peripheral blood of the detected person is quantitatively detected by adopting fluorescence quantitative PCR, a gene expression profiling chip or RNA sequencing technology, and the benign and malignant lung micro-nodules are screened by combining a discrimination model, so that whether the detected person suffers from lung cancer is discriminated, and the early discovery of the lung cancer is realized.

Example 1 peripheral blood characteristic Gene marker screening for Lung cancer

The screening of the lung cancer characteristic gene comprises the following steps:

1) peripheral blood samples were collected from 40 patients with malignant micro-nodules diagnosed with lung cancer by surgery and pathological examination, 16 patients with benign micro-nodules (benign lesions in the lung), and 28 healthy persons without lung lesions. All patients with minimal nodules were confirmed by CT examination to have a nodule size less than or equal to 10mm, and 2-3ml of peripheral blood was collected per sample.

2) Total RNA of the sample is extracted by using a PAXgene Blood RNA Kit extraction Kit, the fragment integrity (RIN) of the RNA sample is detected by an Agilent bioanalyzer 2100 bioanalyzer, and the purity of the RNA sample is detected by a Nano1000 micro ultraviolet spectrophotometer. All RNA samples must meet the following quality control conditions: the RNA yield is more than 2 micrograms, the ratio of 28S/18S peak is more than 1, the RIN value is more than 7, and the absorbance ratio of 260nm/280nm is more than 1.8.

3) Detecting the peripheral blood total RNA sample by adopting an Affymetrix Gene Profiling Array U133Plus2 chip (human whole Gene expression Profiling chip) to obtain peripheral blood Gene expression Profiling data of the sample, then normalizing (normalizing) the peripheral blood Gene expression Profiling data by adopting a MAS5 method in Affymetrix expression Console software, eliminating system errors possibly generated in the detection process of the expression Profiling chip and obtaining peripheral blood Gene expression Profiling data which can be compared uniformly.

4) Eliminating over-high and over-low gene expression signals in the peripheral blood gene expression profile, selecting genes with proper expression (signal value between 100-10000) in all samples to perform T test analysis, comparing peripheral blood gene expression difference of micro-nodule lung cancer with benign nodules and healthy people, and performing subsequent analysis by taking the genes with statistical P value less than 0.05 and gene expression fold change more than 1.1 times as candidate genes.

5) Analyzing the correlation between the candidate genes and the micro-nodular lung cancer, sorting according to the correlation coefficient of the genes and the micro-nodular lung cancer, and selecting a group of gene queues (gene queues I) with high correlation with the micro-nodular lung cancer; in addition, the remaining genes were correlated with the genes in cohort I, and another set of gene cohorts (gene cohort II) with high correlation to gene cohort I was selected. Then pairing the genes in the gene queue I and the gene queue II pairwise to form a series of candidate gene combinations.

6) The method comprises the steps of evaluating the screening effect of each candidate gene combination on the micro-nodular lung cancer by using a logistic regression statistical analysis method, calculating a receiver operator characteristic Curve (ROC) and an Area Under the Curve value (Area Under the Curve) of each candidate gene combination, and screening a series of gene combinations with good screening capability on the micro-nodular lung cancer.

7) The screened serial gene combinations are verified by a real-time fluorescent quantitative PCR method, the genes with consistent expression change in quantitative PCR and gene expression profile chip detection are reserved as peripheral blood characteristic genes of the micro-nodule lung cancer, 12 lung cancer characteristic genes (the gene sequences are shown as SEQ ID NO. 1-SEQ ID NO. 12) of HSP90AA1, UQCRQ, COX7A2, CAPZA2, CHMP5, NDUFB2, RPL24, CKLF, C14orf2, CD52, FGFBP2 and GLRX are mainly screened, and the significance of the 12 lung cancer characteristic genes is shown in FIG. 1.

8) And (3) evaluating the diagnosis effect of any 6 gene combinations selected from the 12 genes on the micro-nodule lung cancer by using a logistic regression statistical analysis method, calculating the ROC AUC of the gene combinations, and establishing a micro-nodule lung cancer discrimination model shown as the following:

wherein, P is the risk value of the micro-nodular lung cancer (malignant lung nodules); b 0-b 6 are the corresponding logistic regression model parameters respectively; delta Ct 1-delta Ct6 are respectively the difference values of the quantitative PCR cycle number Ct values of the 6 micro-nodule lung cancer gene markers and the reference gene; x is a logistic regression log likelihood ratio (log likelihood ratio).

Example 2 detection of micro-Small node Lung cancer Using the selected Lung cancer characteristic Gene markers

1. The method comprises the following steps:

1) collecting peripheral blood samples of the sample to be detected: collecting peripheral blood samples of patients using BD PAXgeneRNA blood collection tubes from QIAGEN;

2) extracting and purifying total RNA in a peripheral blood sample of a sample to be detected: total RNA in peripheral blood was purified by extraction using PAXgeneblood RNAKit from QIAGEN, and the integrity and yield of the extracted total RNA fragments were determined using an Agilent BioAnalyzer model 2100 micro electrophoresis analyzer. Detecting the purity of the RNA sample by using a Nano1000 micro ultraviolet spectrophotometer;

3) reverse transcription reaction: cDNA was synthesized by a Reverse Transcription reaction using a High-Capacity cDNA Reverse Transcription kit of Life Techolgy, using total RNA as a template and Olig (dT) as a Reverse Transcription primer.

4) Fluorescent quantitative RT-PCR detection: according to 6-gene Panel combination products (CKLF, GLRX, HSP90AA1, NDUFB2, RPL24 and UQCRQ which are 6 gene combinations in total) and related sequences of an internal reference gene GAPDH, corresponding specific primers and/or probes are designed or SYBR Green dye capable of being non-specifically combined with PCR amplification fragments is adopted, cDNA obtained by reverse transcription is used as an amplification template, real-time fluorescence quantitative PCR reaction is carried out, and the GAPDH gene is used as the internal reference gene (the amplification primer sequence of the internal reference gene GAPDH is shown as SEQ ID NO. 49-SEQ ID NO.50, the probe sequence is shown as SEQ ID NO. 51), so that the mRNA relative content of the 6 gene markers in peripheral blood samples is obtained. Table 1 below shows the fluorescent quantitative PCR reaction system. The primer and probe sequences designed for the lung cancer signature genes are listed in table 2 below.

TABLE 1 fluorescent quantitative PCR reaction System

Reagent	Concentration of	Volume of
			Primer for characteristic genes of small-nodule lung cancer	800nM	2μL
Fluorescent probe for characteristic gene of micro-nodule lung cancer	200nM	0.5μL
			Internal reference gene GAPDH primer	800nM	2μL
Internal reference gene GAPDH fluorescent probe	200nM	0.5μL
			2×PCR MasterMix		12.5μL
cDNA template	2.67ng/μL	7.5μL
			Total of		25μL

TABLE 2 primer and probe sequences specific for lung cancer signature genes

5) And (3) diagnosis of the result of the sample to be detected: according to the mRNA relative content of the 6 gene markers of CKLF, GLRX, HSP90AA1, NDUFB2, RPL24 and UQCRQ detected by real-time fluorescence quantitative PCR in peripheral blood samples, calculating the logistic regression log-likelihood ratio X value of the samples through corresponding micro-nodule lung cancer discrimination models, and judging that the detection result with the X value being more than or equal to 0 is positive, namely lung cancer; and judging the detection result with the X value of less than 0 as negative, namely judging the non-lung cancer.

2. Results

A total of 144 cases of malignant micro-nodule Lung Cancer (Lung Cancer), 39 cases of Benign micro-nodule (Benign) and 107 cases of healthy people (Health) were collected, the relative expression levels of 6 gene markers of the micro-nodule Lung Cancer and the reference gene GAPDH in the peripheral blood were detected by quantitative fluorescence PCR, the logistic regression log-likelihood ratio X value of each sample was calculated, and a positive detection result was regarded as if the X value was not less than 0, whereas a negative detection result was regarded as if the X value was not less than 0. The detection result is compared with the pathological detection result, the obtained lung cancer characteristic gene marker can better discriminate malignant lung small nodules (micro-nodule lung cancer) and benign micro nodules, the sensitivity and specificity of the lung cancer characteristic gene marker on the micro-nodule lung cancer detection are over 75 percent, and the specific detection result is shown in figure 2.

The above-mentioned embodiments only express the embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Sequence listing

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<400> 6

ctcctggttc aaaagcagct aaaccaaaag aagcctccag acagccctga gatcacctaa 60

aaagctgcta ccaagacagc cacgaagatc ctaccaaaat gaagcgcttc ctcttcctcc 120

tactcaccat cagcctcctg gttatggtac agatacaaac tggactctca ggacaaaacg 180

acaccagcca aaccagcagc ccctcagcat ccagcaacat aagcggaggc attttccttt 240

tcttcgtggc caatgccata atccacctct tctgcttcag ttgaggtgac acgtctcagc 300

cttagccctg tgccccctga aacagctgcc accatcactc gcaagagaat cccctccatc 360

tttgggaggg gttgatgcca gacatcacca ggttgtagaa gttgacaggc agtgccatgg 420

gggcaacagc caaaataggg gggtaatgat gtaggggcca agcagtgccc agctgggggt 480

caataaagtt acccttgtac ttgcaaaaaa aaaaaaaaaa aaa 523

<210> 7

<211> 509

<212> DNA

<213> Intelligent (Homo sapiens)

<400> 7

cgccggggaa gcgaagtagg caggggcgag gcggctgggg accgcggggc ggacgggagc 60

gagtatgtcc gctctgactc ggctggcgtc tttcgctcgc gttggaggcc gccttttcag 120

aagcggctgc gcacggactg ctggagatgg tggagtccgt catgccggtg gtggtgtgca 180

cattgagccc cggtatagac agttccccca gctgaccaga tcccaggtgt tccagagcga 240

gttcttcagc ggactcatgt ggttctggat tctctggcgc ttttggcatg actcagaaga 300

ggtgctgggt cactttccgt atcctgatcc ttcccagtgg acagatgaag aattaggtat 360

ccctcctgat gatgaagact gaaggtgtag actcagcctc actctgtaca agagccaggt 420

gagaatttca aggattatcg acttcatatt gcacattaaa gttacaaatt aaagtggctt 480

ggtcaagaat gagaaaaaaa aaaaaaaaa 509

<210> 8

<211> 2070

<212> DNA

<213> Intelligent (Homo sapiens)

<400> 8

ctgcaggctc tctccgagag caccaagtcc ttttgctctc catccccgga agacccggct 60

gaaaatccgg aaaaagaatc gggaaacgcc aggaggcata ttgcgcttgc gcacggaggg 120

gccggaagtc gaggcgggag tgactctgct tccgtttctg gttttgctct agtgtttggg 180

tttcttcgcg gctgctcaag atgaaccgac tcttcgggaa agcgaaaccc aaggctccgc 240

cgcccagcct gactgactgc attggcacgg tggacagtag agcagaatcc attgacaaga 300

agatttctcg attggatgct gagctagtga agtataagga tcagatcaag aagatgagag 360

agggtcctgc aaagaatatg gtcaagcaga aagccttgcg agttttaaag caaaagagga 420

tgtatgagca gcagcgggac aatcttgccc aacagtcatt caacatggaa caagccaatt 480

ataccatcca gtctttgaag gacaccaaga ccacggttga tgctatgaaa ctgggagtaa 540

aggaaatgaa gaaggcatac aagcaagtga agatcgacca gattgaggat ttacaagacc 600

agctagagga tatgatggaa gatgcaaatg aaatccaaga agcactgagt cgcagttatg 660

gcaccccaga actggatgaa gatgatttag aagcagagtt ggatgcacta ggtgatgagc 720

ttctggctga tgaagacagt tcttatttgg atgaggcagc atctgcacct gcaattccag 780

aaggtgttcc cactgataca aaaaacaagg atggagttct ggtggatgaa tttggattgc 840

cacagatccc tgcttcatag atttgcatca ttcaagcata tcttgtaaaa caaacacata 900

ttatgggact aggaaatatt tatctttcca aatttgccat aacagattta ggtttctttc 960

ctttctttga aggaaagttt aattacattg ctcttttatt ttttccatta agagactcat 1020

tgcttgggaa atgctttctt cgtactaaaa tttgattcct ttttttctta tgaaaaacga 1080

actcagttta aaagtatttt tagctcgtat gacttgtttt cattcattaa taataatttg 1140

aaataaaact aaggaaatgg aatcttaaaa gtctatgaca gtgtaactct acagtctcaa 1200

aatgacctga taaattgata agacaaagat gagattattg gggctgttca tattatgatt 1260

cagaatcatt ttctattgtg gtattatagg ttggttaaag tgatggcctt tttgatgggt 1320

tttgttgtgt cttgtgaaca agtcgttact gtgtccatta ttggaatgga attatcacta 1380

ctgtatcatg agtgggtatt ttgattctat ggttccctca gtattacatc ttgacttgta 1440

atcaattatg aatatttctt gatatttaat gtataggaca tttatttata ctcaataaat 1500

atttttcaaa aggatataat tttaataata tcacttcagc ttaaaacctc tactgcggaa 1560

accaaattta atagaatttt aatgtcattt cagcctataa ctccactaca gaaaccaaat 1620

taaccagtag cattgtgagg aaagagcaag gaacaatctg ggcttgggcc ctgggtctac 1680

catttactaa ctactgagta gtctattcaa cctctctaac cttctgtttc cttattagta 1740

aaatcatgct taactcacag agcttttgtg aggaataatt gaggtaatgg tcataagtac 1800

cttgttaact gcaaggggct attcttatat gagggattgt taacaataaa aaagaaactg 1860

cttcattctt ttcttggaag gtgcctggag tactacagca agttcaaact cctgcccaat 1920

ttcagggtct ttaatgatcc tgtcctccct tcctcattca acttgttgcc aacagcatgg 1980

cccctccagc ctagctgggt gcctcacagt gctatgtgca cctgactctc atgtgtctgc 2040

agatcaaacc aataaacatt taggaacacc 2070

<210> 9

<211> 1090

<212> DNA

<213> Intelligent (Homo sapiens)

<400> 9

attgcattcc tgggcattgc taactagtga agtataccag atggaaatgt cttcgaagct 60

gtccctttaa aactcgagca agctaccagg caaactccgc ctccagggag gttccttatt 120

aaataggagc caactggctg ggtcggggct caatacccca agcaatacct gcaactgagg 180

attcttcccg gggagaccgc agcccatcgg catggctcaa gagtttgtga actgcaaaat 240

ccagcctggg aaggtggttg tgttcatcaa gcccacctgc ccgtactgca ggagggccca 300

agagatcctc agtcaattgc ccatcaaaca agggcttctg gaatttgtcg atatcacagc 360

caccaaccac actaacgaga ttcaagatta tttgcaacag ctcacgggag caagaacggt 420

gcctcgagtc tttattggta aagattgtat aggcggatgc agtgatctag tctctttgca 480

acagagtggg gaactgctga cgcggctaaa gcagattgga gctctgcagt aaccacaggt 540

gagtggcaga tctcatagga aatgttcaac aattctgtga aaggtcacag gacccaattg 600

gagaaatcat atgaaaagca tagttggtct tggtgtcata tggatcagag gcacaagtgc 660

agaggctgtg gtcatgcgga acactctgtt atttaagatg gctatccaga taatcctgaa 720

cactgtgtat ttattttatt tagactacca gcaaagatta aagcatgaaa tgtaaaacat 780

ctgataaaac ttacagcccc ctacaccaag agtgtatctg tgaaagagct cctacacttt 840

gaaaacttaa gaatccctta tcatgaagtt tgcctgttct agaattgtaa gattgttaat 900

ttccttcaat ctctagtgac aacacttaat ttcttttcta ataaaaaaaa cctatagatg 960

attcagtgat ttttgtccaa ttcatttgca tgttctcaag acattaagga atgttatgcg 1020

aaatacacta acttaaaact gtgtttatat ttggccctgc cattataaat aaagacacgt 1080

gctgctgtca 1090

<210> 10

<211> 3887

<212> DNA

<213> Intelligent (Homo sapiens)

<400> 10

gactgcgcag gcgtgctcac ctggcgtgct ccacccgact gggcgtccgc aggctcctcc 60

cccgggtgtg gcctccgggc ggcatggctg cttcccaggt gatgccggct tcagctagtg 120

gggtctagtt gaccgttccg cagccgccag ggccagcgga aagccggtca gggggaaccg 180

cggcggggct ggtgtcatga gcctgaggtg aacttgaggg tgcctcctca gcggtctccc 240

gccctgccct gaggggcgcc gggaccccaa agagcggagg aagagcgcca ccccgacggc 300

caccgcttcg gagccagcac gcggggtacc ctacggggag cgcggatgcc cccgtgttcg 360

ggcggggacg gctccacccc tcctgggccc tcccttcggg acagggactg tcccgcccag 420

agtgctgaat acccgcgcga ccgtctggat ccccgcccag gaagcccctc tgaagcctcc 480

tcgccgccgt ttctgagaag cagggcacct gttaactggt accaagaaaa ggcccaagtg 540

tttctctggc atctgatggt gtctggatcc accactctac tctgtctctg gaaacagccc 600

ttccacgtct ctgcattccc tgtcaccgcg tcactggcct tcagacagag ccaaggtgca 660

gggcaacacc tctacaagga tctgcagcca tttatattgc ttaggctact gatgcctgag 720

gaaacccaga cccaagacca accgatggag gaggaggagg ttgagacgtt cgcctttcag 780

gcagaaattg cccagttgat gtcattgatc atcaatactt tctactcgaa caaagagatc 840

tttctgagag agctcatttc aaattcatca gatgcattgg acaaaatccg gtatgaaagc 900

ttgacagatc ccagtaaatt agactctggg aaagagctgc atattaacct tataccgaac 960

aaacaagatc gaactctcac tattgtggat actggaattg gaatgaccaa ggctgacttg 1020

atcaataacc ttggtactat cgccaagtct gggaccaaag cgttcatgga agctttgcag 1080

gctggtgcag atatctctat gattggccag ttcggtgttg gtttttattc tgcttatttg 1140

gttgctgaga aagtaactgt gatcaccaaa cataacgatg atgagcagta cgcttgggag 1200

tcctcagcag ggggatcatt cacagtgagg acagacacag gtgaacctat gggtcgtgga 1260

acaaaagtta tcctacacct gaaagaagac caaactgagt acttggagga acgaagaata 1320

aaggagattg tgaagaaaca ttctcagttt attggatatc ccattactct ttttgtggag 1380

aaggaacgtg ataaagaagt aagcgatgat gaggctgaag aaaaggaaga caaagaagaa 1440

gaaaaagaaa aagaagagaa agagtcggaa gacaaacctg aaattgaaga tgttggttct 1500

gatgaggaag aagaaaagaa ggatggtgac aagaagaaga agaagaagat taaggaaaag 1560

tacatcgatc aagaagagct caacaaaaca aagcccatct ggaccagaaa tcccgacgat 1620

attactaatg aggagtacgg agaattctat aagagcttga ccaatgactg ggaagatcac 1680

ttggcagtga agcatttttc agttgaagga cagttggaat tcagagccct tctatttgtc 1740

ccacgacgtg ctccttttga tctgtttgaa aacagaaaga aaaagaacaa catcaaattg 1800

tatgtacgca gagttttcat catggataac tgtgaggagc taatccctga atatctgaac 1860

ttcattagag gggtggtaga ctcggaggat ctccctctaa acatatcccg tgagatgttg 1920

caacaaagca aaattttgaa agttatcagg aagaatttgg tcaaaaaatg cttagaactc 1980

tttactgaac tggcggaaga taaagagaac tacaagaaat tctatgagca gttctctaaa 2040

aacataaagc ttggaataca cgaagactct caaaatcgga agaagctttc agagctgtta 2100

aggtactaca catctgcctc tggtgatgag atggtttctc tcaaggacta ctgcaccaga 2160

atgaaggaga accagaaaca tatctattat atcacaggtg agaccaagga ccaggtagct 2220

aactcagcct ttgtggaacg tcttcggaaa catggcttag aagtgatcta tatgattgag 2280

cccattgatg agtactgtgt ccaacagctg aaggaatttg aggggaagac tttagtgtca 2340

gtcaccaaag aaggcctgga acttccagag gatgaagaag agaaaaagaa gcaggaagag 2400

aaaaaaacaa agtttgagaa cctctgcaaa atcatgaaag acatattgga gaaaaaagtt 2460

gaaaaggtgg ttgtgtcaaa ccgattggtg acatctccat gctgtattgt cacaagcaca 2520

tatggctgga cagcaaacat ggagagaatc atgaaagctc aagccctaag agacaactca 2580

acaatgggtt acatggcagc aaagaaacac ctggagataa accctgacca ttccattatt 2640

gagaccttaa ggcaaaaggc agaggctgat aagaacgaca agtctgtgaa ggatctggtc 2700

atcttgcttt atgaaactgc gctcctgtct tctggcttca gtctggaaga tccccagaca 2760

catgctaaca ggatctacag gatgatcaaa cttggtctgg gtattgatga agatgaccct 2820

actgctgatg ataccagtgc tgctgtaact gaagaaatgc caccccttga aggagatgac 2880

gacacatcac gcatggaaga agtagactaa tctctggctg agggatgact tacctgttca 2940

gtactctaca attcctctga taatatattt tcaaggatgt ttttctttat ttttgttaat 3000

attaaaaagt ctgtatggca tgacaactac tttaagggga agataagatt tctgtctact 3060

aagtgatgct gtgatacctt aggcactaaa gcagagctag taatgctttt tgagtttcat 3120

gttggtttat tttcacagat tggggtaacg tgcactgtaa gacgtatgta acatgatgtt 3180

aactttgtgg tctaaagtgt ttagctgtca agccggatgc ctaagtagac caaatcttgt 3240

tattgaagtg ttctgagctg tatcttgatg tttagaaaag tattcgttac atcttgtagg 3300

atctactttt tgaacttttc attccctgta gttgacaatt ctgcatgtac tagtcctcta 3360

gaaataggtt aaactgaagc aacttgatgg aaggatctct ccacagggct tgttttccaa 3420

agaaaagtat tgtttggagg agcaaagtta aaagcctacc taagcatatc gtaaagctgt 3480

tcaaaaataa ctcagaccca gtcttgtgga tggaaatgta gtgctcgagt cacattctgc 3540

ttaaagttgt aacaaataca gatgagttaa aagatattgt gtgacagtgt cttatttagg 3600

gggaaagggg agtatctgga tgacagttag tgccaaaatg taaaacatga ggcgctagca 3660

ggagatggtt aaacactagc tgctccaagg gttgacatgg tcttcccagc atgtactcag 3720

caggtgtggg gtggagcaca cgtaggcaca gaaaacagga atgcagacaa catgcatccc 3780

ctgcgtccat gagttacatg tgttctctta gtgtccacgt tgttttgatg ttattcatgg 3840

aataccttct gtgttaaata cagtcactta attccttggc cttaaaa 3887

<210> 11

<211> 2373

<212> DNA

<213> Intelligent (Homo sapiens)

<400> 11

cccctccctt agcgggggcg cgcggcgctg aggaccgcac ggaaacgggg aagtcaggtg 60

gccgctgccg ccgccgccgc cgcggtttgt cgccagaagg aagatggcgg atctggagga 120

gcagttgtct gatgaagaga aggtgcgtat agcagcaaaa ttcatcattc atgcccctcc 180

tggagaattt aatgaggttt tcaatgatgt tcggttactg cttaataatg acaatcttct 240

cagggaagga gcagcccatg catttgcaca gtataacttg gaccagttta ctccagtaaa 300

aattgaaggt tatgaagatc aggtattgat aacagaacat ggcgacttgg gaaatggaaa 360

gtttttggat ccaaagaaca gaatctgttt taaatttgat cacttaagga aggaggcaac 420

tgatccaaga ccctgtgaag tagaaaatgc agttgaatca tggagaactt cagtagaaac 480

tgctctgaga gcttacgtaa aagaacatta cccgaatgga gtctgcactg tgtatggcaa 540

aaaaatagat ggacagcaaa ccattattgc atgcatagaa agccatcagt tccaagcaaa 600

aaatttttgg aatggtcgtt ggaggtcaga atggaagttt acaatcactc cttcaaccac 660

tcaagtggtt ggcatcttga aaattcaggt tcattattat gaagatggta atgttcagct 720

agtgagtcat aaagatatac aagattccct aacagtgtct aatgaagtgc aaacagcaaa 780

agaatttata aagattgtag aagctgcaga aaatgaatac cagactgcca tcagtgagaa 840

ttatcagaca atgtcggaca ctactttcaa agccttacgt cgacagttgc cagttacacg 900

cactaagatt gattggaaca agatccttag ctacaagatt ggcaaagaga tgcagaatgc 960

ataagatgaa cattgcatga ccggatcatt ttagtgtctt tgcgttaaaa aatcattgca 1020

aaagtattct gaactgtcaa gctgcccagt cagatgggct gttgccattt aaaatcactg 1080

taattaatta gtttgattag agcacaaagc ttagctaatc aaccattatt tttcattttg 1140

tttgttctaa gaggattgaa aatcagttta gtttaaatgt ctttctgtta ggcctttctt 1200

tcttacaatg aagagatgat tcttctagtt tatggttaaa agtttttgaa gtgtctcaaa 1260

aatattttac taactgtaac cctaaaattg atgtcttttg gtttatgaaa tcagtaattt 1320

ttgatatttc cccagttctt tttaatgggg tcaataatgg acattctagt ttaaggtggt 1380

tgatggattt agccatatat gctgctaaag aaattgtcta ccttttcttc ctcacctgtt 1440

ccatttatgt aaagttgaga ttagagggaa agcattttct atatcaattg tgtttaaacc 1500

tttcaagaag gttatttagc tagcttagtg ttgaactaaa ttttttttaa acaaggcaag 1560

gtctaatgct gttttgagat tctgaaatta atgaaaatac ttatttcaga aatgcattta 1620

atgctttttt tcttgtgaca gttacgcaaa tcagcttgaa ttccatatgt ccctgagtta 1680

tttttatcat aaagccacaa atgtattata acaaggcaaa ttgtaatata tataatcctg 1740

aactcatgac catgtctcgg tttatttttt ttttcttgga ttgaaaagta ctgaaattca 1800

atgtgacatt aaaatgcaaa ttttcctatt tatttgagta gaaaatcact taccagtgag 1860

catatatatt ttaaaatact ttctttggat attgtaattc ttaactggtt gtaaattaga 1920

aaagctggga ttacatatgg tgtgcggtta cagtctaaat tttttcatcc tcctatgcat 1980

cataagcatg tttgtaatat tttcaaaaat agttctactg atgctacagg aatttcaagc 2040

ctgtggtgaa tgttagtatt taccataggg agtgaagtgg agttatggtt tcattcaata 2100

gagtattgct gattatactt gagtggaatc ctttcctcac gtactcccac agacgtctgg 2160

gcctggaaat ttttttttta ttttatttta ttgttttttt ttttagaaaa acaccacttt 2220

tattatgtac aataaaatat ttcattagct tgaattgtat agatttttaa aaattcaatg 2280

aaagcatgtt gtttaatttc tttttaaaat cactgttggg ctttgaaagc attgagaata 2340

taatatgaaa ttatgaaaaa aaaaaaaaaa aaa 2373

<210> 12

<211> 579

<212> DNA

<213> Intelligent (Homo sapiens)

<400> 12

tctttctttt cgccatcttt tgtctttccg tggagctgtc gccatgaagg tcgagctgtg 60

cagttttagc gggtacaaga tctaccccgg acacgggagg cgctacgcca ggaccgacgg 120

gaaggttttc cagtttctta atgcgaaatg cgagtcggct ttcctttcca agaggaatcc 180

tcggcagata aactggactg tcctctacag aaggaagcac aaaaagggac agtcggaaga 240

aattcaaaag aaaagaaccc gccgagcagt caaattccag agggccatta ctggtgcatc 300

tcttgctgat ataatggcca agaggaatca gaaacctgaa gttagaaagg ctcaacgaga 360

acaagctatc agggctgcta aggaagcaaa aaaggctaag caagcatcta aaaagactgc 420

aatggctgct gctaaggcac ctacaaaggc agcacctaag caaaagattg tgaagcctgt 480

gaaagtttca gctccccgag ttggtggaaa acgctaaact ggcagattag atttttaaat 540

aaagattgga ttataactct agaaaaaaaa aaaaaaaaa 579

<210> 13

<211> 23

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 13

caccagaatg aaggagaacc aga 23

<210> 14

<211> 22

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 14

aagacgttcc acaaaggctg ag 22

<210> 15

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 15

actaaaggaa tccccaatgt tctg 24

<210> 16

<211> 25

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 16

aagataaaac actacaaact gcggc 25

<210> 17

<211> 22

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 17

tggtcagtaa cagccaagat gc 22

<210> 18

<211> 21

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 18

tatcgtcctc tgcccaatct g 21

<210> 19

<211> 22

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 19

agaaagccat cagttccaag ca 22

<210> 20

<211> 23

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 20

ccacttgagt ggttgaagga gtg 23

<210> 21

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 21

gaacaagcca attataccat ccag 24

<210> 22

<211> 25

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 22

atgccttctt catttccttt actcc 25

<210> 23

<211> 21

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 23

ttcagcggac tcatgtggtt c 21

<210> 24

<211> 22

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 24

catctgtcca ctgggaagga tc 22

<210> 25

<211> 23

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 25

acaatctttt gcttaggtgc tgc 23

<210> 26

<211> 25

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 26

caaaaaaggc taagcaagca tctaa 25

<210> 27

<211> 20

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 27

ccgtcggcaa gacagcatac 20

<210> 28

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 28

ggcactgata ccagaaacca caac 24

<210> 29

<211> 20

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 29

gctgcagatt tgtggtgcgt 20

<210> 30

<211> 23

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 30

ggcttcatgg ggatccatat gtt 23

<210> 31

<211> 21

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 31

agaaaaggaa aatgcctccg c 21

<210> 32

<211> 25

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 32

gcctcctggt tatggtacag ataca 25

<210> 33

<211> 20

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 33

gcctgggaac attgttggaa 20

<210> 34

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 34

tcagggagag gtcagatctg tagg 24

<210> 35

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 35

gcatccgcct atacaatctt tacc 24

<210> 36

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 36

caagattatt tgcaacagct cacg 24

<210> 37

<211> 29

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 37

agctacctgg tccttggtct cacctgtga 29

<210> 38

<211> 25

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 38

ccgcattcgg gagtctttct ttcgc 25

<210> 39

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 39

acgaagagcc agcagattcc gcag 24

<210> 40

<211> 27

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 40

tccattctga cctccaacga ccattcc 27

<210> 41

<211> 27

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 41

catcaaccgt ggtcttggtg tccttca 27

<210> 42

<211> 28

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 42

aagaggtgct gggtcacttt ccgtatcc 28

<210> 43

<211> 28

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 43

tttgtaggtg ccttagcagc agccattg 28

<210> 44

<211> 26

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 44

ctgtcacaag tgcaaacacc cctcca 26

<210> 45

<211> 22

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 45

ctgagccgtc tgtcctgcgc ca 22

<210> 46

<211> 23

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 46

ctgaggggct gctggtttgg ctg 23

<210> 47

<211> 20

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 47

cccttccagg ccctgtgcgc 20

<210> 48

<211> 23

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 48

ctcgaggcac cgttcttgct ccc 23

<210> 49

<211> 24

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 49

accatgagaa gtatgacaac agcc 24

<210> 50

<211> 23

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 50

cacgatacca aagttgtcat gga 23

<210> 51

<211> 23

<212> DNA

<213> Artificial Sequence (Artificial Sequence)

<400> 51

tcagcaatgc ctcctgcacc acc 23

Claims (10)

1. A polynucleotide combination product is characterized by consisting of polynucleotides shown in sequences SEQ ID NO.1, SEQ ID NO.2, SEQ ID NO.6, SEQ ID NO.7, SEQ ID NO.8 and SEQ ID NO.12, wherein the polynucleotides are differentially expressed in peripheral blood of patients with minimal node lung cancer and patients with non-lung cancer, and the polynucleotides are lung cancer characteristic gene markers.

2. The composition comprises a primer and/or a probe for detecting gene differential expression in peripheral blood of a patient with the micro-nodular lung cancer and a patient with the non-lung cancer, wherein the gene sequence of the differential expression is a lung cancer characteristic gene sequence shown in SEQ ID NO.1, SEQ ID NO.2, SEQ ID NO.6, SEQ ID NO.7, SEQ ID NO.8 and SEQ ID NO. 12.

3. Use of a combination product according to claim 1 for the preparation of a product for the differential diagnosis or screening of very early lung cancer.

4. The use of claim 3, wherein the product for differentially diagnosing or screening for very early lung cancer comprises: and detecting the product of the micro-nodular lung cancer by using real-time quantitative PCR, RNA sequencing or gene chips.

5. The use as claimed in claim 4, wherein the product for differentially diagnosing or screening the very early lung cancer by real-time quantitative PCR comprises primers for specifically amplifying the lung cancer characteristic gene sequences shown in SEQ ID No.1, SEQ ID No.2, SEQ ID No.6, SEQ ID No.7, SEQ ID No.8 and SEQ ID No. 12.

6. The use of claim 4, wherein the products for the differential diagnosis or screening of the ultra-early lung cancer by gene chip detection comprise: specific probes hybridized with the lung cancer characteristic gene sequences shown in SEQ ID NO.1, SEQ ID NO.2, SEQ ID NO.6, SEQ ID NO.7, SEQ ID NO.8 and SEQ ID NO. 12.

7. A detection kit for differential diagnosis or screening of ultra-early lung cancer is characterized by comprising primers and/or probes specific to lung cancer characteristic gene sequences shown in SEQ ID NO.1, SEQ ID NO.2, SEQ ID NO.6, SEQ ID NO.7, SEQ ID NO.8 and SEQ ID NO. 12.

8. The detection kit according to claim 7, wherein the primer has a nucleotide sequence shown in SEQ ID No. 13-16, SEQ ID No. 23-28, and SEQ ID No. 35-36.

9. The detection kit according to claim 7, wherein the probe has a nucleotide sequence shown in SEQ ID No. 37-38, SEQ ID No. 42-44, and SEQ ID No. 48.

10. A detection chip for differential diagnosis or screening of ultra-early lung cancer is characterized by comprising a specific probe hybridized with a lung cancer characteristic gene sequence shown in SEQ ID NO.1, SEQ ID NO.2, SEQ ID NO.6, SEQ ID NO.7, SEQ ID NO.8 and SEQ ID NO. 12.

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